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A Computer-Assisted Analysis System for Mathematical Programming Models and Solutions, H.J. Greenberg


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Автор: H.J. Greenberg
Название:  A Computer-Assisted Analysis System for Mathematical Programming Models and Solutions
ISBN: 9781461364283
Издательство: Springer
Классификация:


ISBN-10: 1461364280
Обложка/Формат: Paperback
Страницы: 270
Вес: 0.41 кг.
Дата издания: 19.04.2013
Серия: Operations Research/Computer Science Interfaces Series
Язык: English
Размер: 234 x 156 x 15
Основная тема: Mathematics
Подзаголовок: A User’s Guide for ANALYZE©
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Welcome to ANALYZE, designed to provide computer assistance for analyzing linear programs and their solutions. Chapter 4 goes through some elementary exercises to demonstrate computer- assisted analysis and introduce additional conventions of the ANALYZE language.


Mathematical Methods and Models in Economic Planning, Management and Budgeting

Автор: Galimkair Mutanov
Название: Mathematical Methods and Models in Economic Planning, Management and Budgeting
ISBN: 3662451417 ISBN-13(EAN): 9783662451410
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This book describes a system of mathematical models and methods that can be used to analyze real economic and managerial decisions and to improve their effectiveness.

Model Building in Mathematical Programming

Автор: Williams H Paul
Название: Model Building in Mathematical Programming
ISBN: 1118443330 ISBN-13(EAN): 9781118443330
Издательство: Wiley
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Цена: 7437.00 р.
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Описание: The 5th edition of Model Building in Mathematical Programming discusses the general principles of model building in mathematical programming and demonstrates how they can be applied by using several simplified but practical problems from widely different contexts.

New Trends in Mathematical Programming

Автор: F. Giannessi; S?ndor Koml?si; Tam?s Rapcs?k
Название: New Trends in Mathematical Programming
ISBN: 1441947930 ISBN-13(EAN): 9781441947932
Издательство: Springer
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Цена: 23058.00 р.
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Описание: Though the volume covers 22 papers by 36 authors from 12 countries, the history in the background is bound to Hungary where, in 1973 Andras Pnkopa started to lay the foundation of a scientific forum, which can be a regular meeting spot for experts of the world in the field.

Progress in Mathematical Programming

Автор: Nimrod Megiddo
Название: Progress in Mathematical Programming
ISBN: 1461396190 ISBN-13(EAN): 9781461396192
Издательство: Springer
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Цена: 14673.00 р.
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Описание: The starting point of this volume was a conference entitled "Progress in Mathematical Programming," held at the Asilomar Conference Center in Pacific Grove, California, March 1-4, 1987. The main topic of the conference was developments in the theory and practice of linear programming since Karmarkar's algorithm. There were thirty presentations and approximately fifty people attended. Presentations included new algorithms, new analyses of algorithms, reports on computational experience, and some other topics related to the practice of mathematical programming. Interestingly, most of the progress reported at the conference was on the theoretical side. Several new polynomial algorithms for linear program- ming were presented (Barnes-Chopra-Jensen, Goldfarb-Mehrotra, Gonzaga, Kojima-Mizuno-Yoshise, Renegar, Todd, Vaidya, and Ye). Other algorithms presented were by Betke-Gritzmann, Blum, Gill-Murray-Saunders-Wright, Nazareth, Vial, and Zikan-Cottle. Efforts in the theoretical analysis of algo- rithms were also reported (Anstreicher, Bayer-Lagarias, Imai, Lagarias, Megiddo-Shub, Lagarias, Smale, and Vanderbei). Computational experiences were reported by Lustig, Tomlin, Todd, Tone, Ye, and Zikan-Cottle. Of special interest, although not in the main direction discussed at the conference, was the report by Rinaldi on the practical solution of some large traveling salesman problems. At the time of the conference, it was still not clear whether the new algorithms developed since Karmarkar's algorithm would replace the simplex method in practice. Alan Hoffman presented results on conditions under which linear programming problems can be solved by greedy algorithms.

Mathematical Introduction to Linear Programming and Game Theory

Автор: Louis Brickman
Название: Mathematical Introduction to Linear Programming and Game Theory
ISBN: 146128869X ISBN-13(EAN): 9781461288695
Издательство: Springer
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Цена: 6986.00 р.
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Описание: Mathematical elegance is a constant theme in this treatment of linear programming and matrix games. This thorough introduction to linear programming and game theory will impart a deep understanding of the material and also increase the student`s mathematical maturity.

Nondifferentiable and Two-Level Mathematical Programming

Автор: Kiyotaka Shimizu; Yo Ishizuka; Jonathan F. Bard
Название: Nondifferentiable and Two-Level Mathematical Programming
ISBN: 0792398211 ISBN-13(EAN): 9780792398219
Издательство: Springer
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Цена: 30606.00 р.
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Описание: Provides an exposition of the techniques that are available for optimizing complex systems and to do so in a way that unifies the theory of nondifferentiable and two-level mathematical programming. This book also points out the useful algorithms developed for solving a particular instance of two-level problem known as a static Stackelberg game.

Entropy Optimization and Mathematical Programming

Автор: Shu-Cherng Fang; J.R. Rajasekera; H.S.J. Tsao
Название: Entropy Optimization and Mathematical Programming
ISBN: 0792399390 ISBN-13(EAN): 9780792399391
Издательство: Springer
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Цена: 30606.00 р.
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Описание: Entropy optimization is a useful combination of classical engineering theory (entropy) with mathematical optimization. A systematic presentation with proper mathematical treatment of this material is needed in all application areas. The purpose of this book is to meet this need.

Redundancy in Mathematical Programming

Автор: M.H. Karwan; M.H. Karwan; V. Lotfi; J. Telgen; S.
Название: Redundancy in Mathematical Programming
ISBN: 3540115528 ISBN-13(EAN): 9783540115526
Издательство: Springer
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Цена: 15372.00 р.
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Описание: With contributions by numerous experts

Decomposition Techniques in Mathematical Programming

Автор: Antonio J. Conejo; Enrique Castillo; Roberto Mingu
Название: Decomposition Techniques in Mathematical Programming
ISBN: 3642066070 ISBN-13(EAN): 9783642066078
Издательство: Springer
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Цена: 22201.00 р.
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Описание: Optimization plainly dominates the design, planning, operation, and c- trol of engineering systems. This is a book on optimization that considers particular cases of optimization problems, those with a decomposable str- ture that can be advantageously exploited. Those decomposable optimization problems are ubiquitous in engineering and science applications. The book considers problems with both complicating constraints and complicating va- ables, and analyzes linear and nonlinear problems, with and without in- ger variables. The decomposition techniques analyzed include Dantzig-Wolfe, Benders, Lagrangian relaxation, Augmented Lagrangian decomposition, and others. Heuristic techniques are also considered. Additionally, a comprehensive sensitivity analysis for characterizing the solution of optimization problems is carried out. This material is particularly novel and of high practical interest. This book is built based on many clarifying, illustrative, and compu- tional examples, which facilitate the learning procedure. For the sake of cl- ity, theoretical concepts and computational algorithms are assembled based on these examples. The results are simplicity, clarity, and easy-learning. We feel that this book is needed by the engineering community that has to tackle complex optimization problems, particularly by practitioners and researchersinEngineering, OperationsResearch, andAppliedEconomics.The descriptions of most decomposition techniques are available only in complex and specialized mathematical journals, di?cult to understand by engineers. A book describing a wide range of decomposition techniques, emphasizing problem-solving, and appropriately blending theory and application, was not previously available.

Fuzzy Mathematical Programming and Fuzzy Matrix Games

Автор: C. R. Bector; Suresh Chandra
Название: Fuzzy Mathematical Programming and Fuzzy Matrix Games
ISBN: 3642062652 ISBN-13(EAN): 9783642062650
Издательство: Springer
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Цена: 19589.00 р.
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Описание: Game theory has already proved its tremendous potential for con?ict resolution problems in the ?elds of Decision Theory and Economics. The objective of this book is to present a systematic and focussed study of the application of fuzzy sets to two very basic areas of decision theory, namely Mathematical Programming and Matrix Game Theory.

Algorithmic Principles of Mathematical Programming

Автор: Ulrich Faigle; W. Kern; G. Still
Название: Algorithmic Principles of Mathematical Programming
ISBN: 9048161177 ISBN-13(EAN): 9789048161171
Издательство: Springer
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Цена: 12157.00 р.
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Описание: Algorithmic Principles of Mathematical Programming investigates the mathematical structures and principles underlying the design of efficient algorithms for optimization problems. Recent advances in algorithmic theory have shown that the traditionally separate areas of discrete optimization, linear programming, and nonlinear optimization are closely linked. This book offers a comprehensive introduction to the whole subject and leads the reader to the frontiers of current research. The prerequisites to use the book are very elementary. All the tools from numerical linear algebra and calculus are fully reviewed and developed. Rather than attempting to be encyclopedic, the book illustrates the important basic techniques with typical problems. The focus is on efficient algorithms with respect to practical usefulness. Algorithmic complexity theory is presented with the goal of helping the reader understand the concepts without having to become a theoretical specialist. Further theory is outlined and supplemented with pointers to the relevant literature.
The book is equally suited for self-study for a motivated beginner and for a comprehensive course on the principles of mathematical programming within an applied mathematics or computer science curriculum at advanced undergraduate or graduate level. The presentation of the material is such that smaller modules on discrete optimization, linear programming, and nonlinear optimization can easily be extracted separately and used for shorter specialized courses on these subjects.

Stochastic Versus Fuzzy Approaches to Multiobjective Mathematical Programming under Uncertainty

Автор: Shi-Yu Huang; Jaques Teghem
Название: Stochastic Versus Fuzzy Approaches to Multiobjective Mathematical Programming under Uncertainty
ISBN: 9401074496 ISBN-13(EAN): 9789401074490
Издательство: Springer
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Цена: 41647.00 р.
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Описание: Lastly the constraints, expressed by equalities or inequalities between linear expressions, are often softer in reality that what their mathematical expression might let us believe, and infeasibility as detected by the linear programming techniques can often been coped with by making trade-offs with the real world.


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